Courses & research

During your Master’s in Applied Mathematics, you will collect a total of 120 EC within two years. In addition to the three compulsory courses that form the core of this Master's, you will follow additional courses within the specialisation in Mathematics of Data Science & AI (MDS&AI). The second year consists of additional courses, an internship, and your master’s thesis. Together with your specialisation supervisor, you will draw up a course list tailored to your interests to best prepare you for a specific thesis topic.

European Credit Transfer System

Student workload at Dutch universities is expressed in EC, also named ECTS (European Credit Transfer and Accumulation System), which is widely used throughout the European Union. In the Netherlands, each credit represents 28 hours of work.

Contents of year 1

First year
Compulsory courses for the Master's in AM	17 EC	Continuous Optimization (mastermath course) Scientific Computing Pioneers of Applied Mathematics
Compulsory courses for the specialisation in Mathematics of Data Science & AI	10 EC	Statistical Learning Managing Big Data
Alignment courses If you’re missing either a mathematical or computer science background, your personalised study programme will include alignment courses as part of the specialisation.	Up to 14 EC	Information & Hardware Linear Structures 1 Introduction to Mathematical Analysis Optimisation Basics
Elective specialisation courses You will fill up the rest of your first year and 15 EC of your second year with elective courses. In addition to courses offered at UT, mastermath courses can be chosen as electives.	Up to 33 EC	Deep Learning: from Theory to Practice Graphical Models and Causality Markov Decision Theory and Algorithmic Methods Reinforcement Learning Measure and Probability Spatial Statistics Uncertainty Quantification and Data-driven Modeling E-values and Game-Theoretic Statistics Foundation Models Inverse Problems in Imaging Deep Learning in Medical Image Analysis
Total EC first year	60 EC

or meet online with a student and gain first-hand experience!

Contents of year 2

Second year
Elective specialisation courses	15 EC	You will finish the remaining set of elective courses in the second year.
Internship	15 EC	In the second year, you will do an internship preparing you for the professional field.
Master's thesis	30 EC	In the final three quarters, you will join a research group to complete your master’s thesis.
Total EC of second year	60 EC

Internship

In the second year of your Master’s in Applied Mathematics, you will do an internship. That way, you can apply the knowledge and skills you have acquired during your studies at a company that profits from a structured look into data science and artificial intelligence. The EEMCS faculty at the University of Twente has connections with numerous research institutes and organisations, including tech companies, consulting agencies, banks, insurance companies, the finance and energy industries, and the IT sector, where you can complete your internship.

Previous students have done internships at:

companies that are centred around the use of data, like Booking.com, Uber, or Google.
tech companies like Philips or Thales that are using new developments in data science and artificial intelligence to improve their products
consulting companies, like Witteveen+Bos, or PWC
government and research organisations, like Kadaster, the Royal Netherlands Meteorological Institute, and Deltares

Apart from the above, an internship at a foreign university is also a possibility. Based on what you wish to learn and how you see your future, you and your coordinator together will determine the choice that best suits your situation and preferences.

Master's thesis

You will complete your Master’s by writing your master’s thesis. The choice of your thesis topic is largely up to you. You will have the opportunity to contribute to high-end research at UT. Your article might even get published, as proven by the numerous publications of our former students.

As part of your master’s thesis, you can undertake a research project such as:

Can you use graph neural networks to estimate blood flow parameters such as wall shear stress and blood pressure more quickly in bifurcating coronary arteries?
Can you develop a rigorous theory to make statistical statements about the existence of exoplanets? And, based on this can you derive optimal data-driven methods to search suitable databases for exoplanets?
Can deep neural networks beat time series analysis at identifying structural changes in temporal data?

Career perspectives